Shopping Behavior Research Articles

Online Shopping Behaviour and User Experience Using Machine Learning

Building upon prior research, this project investigates online shopping behavior and user experience using machine learning. The objective is to refine e- commerce interactions through data analysis, aiming for improved personalization and user satisfaction. The researcher plans to implement a common but impact change by enhancing recommendation algorithms. The primary languages for project development include Python for machine learning models and data analysis, and We are planning to make our shopping suggestions even smarter by tweaking how they work. It's kind of like adding a pinch of extra flavor to our online shopping experience. To make all this happen, we'll be using languages like Python.

The Role of Last-Mile Delivery Quality and Satisfaction in Online Retail Experience: An Empirical Analysis

The rise of the e-commerce industry has markedly changed the global economy, providing customers with unparalleled access to goods and services. This study empirically examines online shoppers’ perceptions and preferences, focusing on their experiences with last-mile delivery (LMD) services and its impact on their shopping behaviour. This research employs machine learning classification and regression models for a large-scale analysis of customers’ responses, collected using an online survey in the main cities in Saudi Arabia, which is experiencing rapid e-commerce growth amidst a broader digital transformation. The findings highlight a strong consumer preference for timely LMD services, typically within a day of purchase, while noting dissatisfaction with exceedingly early delivery windows. The research emphasises the need to address customer dissatisfaction with delivery services to retain clientele, as many may switch retailers without informing the retailers. Additionally, a considerable trend towards preferring digital over cash-on-delivery payment methods was observed among online shoppers. Overall, this study provides valuable insights into the significant influence of LMD services on customer satisfaction and behaviour in the e-commerce sector. The use of robust machine learning models has revealed critical factors that can guide retailers and LMD providers in enhancing service delivery and customer experience, contributing to the broader discourse on e-commerce logistics efficiency and customer satisfaction.

CONSUMER SHOPPING BEHAVIOR IN INDONESIA AND THAILAND: HEDONIC AND UTILITARIAN SHOPPING VALUES

Introduction: Shopping value, which influences shopping experiences, has garnered attention and constitutes a well-studied topic in marketing. This study aimed to measure and describe differences in consumer shopping behavior between Thailand and Indonesia regarding hedonic and utilitarian values. Methods: This study employed a quantitative, descriptive, cross-sectional survey conducted among consumers residing in Indonesia and Thailand. The respondents comprised 70 individuals aged 18 years from Surakarta City and an equivalent number from Nonthaburi City. The data distribution and collection using questionnaires were carried out for 2 months, from July to August 2023. The data analysis was performed by utilizing SPSS software. Notably, both cities are in the process of rapid development into metropolises. Most respondents were women under 25 years old. Results: This study discovered that Indonesian and Thai consumers performed hedonic shopping behaviors. However, consumers with hedonic shopping behaviors in Thailand were more inclined towards impulsive shopping behaviors and engaged in shopping activities out of desire rather than necessity, compared to consumers in Indonesia. Conclusion and suggestion: This study described that both Indonesian and Thai consumers had utilitarian shopping behaviors, enabling them to accomplish their objectives and procure desired items effectively during shopping endeavors. Nonetheless, consumers in Thailand display a tendency to find their desired items and prefer to shop briefly compared to their counterparts in Indonesia. Future researchers would benefit from examining the relationship between consumer behavior and other factors such as age or gender. Understanding the influence of these variables on shopping behavior is crucial for gaining comprehensive insights into consumer preferences and decision-making processes in the retail environment.

A STUDY ON CONSUMERS' INTENTIONS TO REUSE MOBILE APPAREL APPLICATIONS

To understand how hedonic shopping orientation affects the desire to reuse mobile applications, this study will examine the mediating role of the need for mobile app atmosphere as well as the moderating role of mobile irritation. 222 consumers who used mobile applications for their shopping provided information via an online survey. Process Macro testing was done on the research model. The test results indicate that there is a strong beneficial impact of hedonic shopping orientation on the intention to reuse mobile apps. Simultaneously, hedonic shopping orientation has a considerable impact on the intention to reuse mobile apps due to the positive mediating role of the need for mobile app atmosphere and the negative moderating influence of mobile irritation. This study presents implications for mobile app retailing and expands the field of research on mobile shopping behavior. Important information is also provided for mobile customers who have a hedonic shopping orientation.

Exploratory Insights into Cross-Cultural Online Shopping Differences between U.S. and French Millennials and Generation Zs

Online retail sales have shown double-digit growth in the U.S. for the last decade, lead by millennials and, more recently, generation Z. While extensive research has been done exploring U.S. online shopping behaviors of these generations, little cross-cultural work has been done. This paper explores the differences between the U.S. and French millennial and generation Z online shoppers. The research focused on four questions; was there a difference in the number of times per week that individuals shopped online, the percentage of shopping funds spent online versus in-store, the types of products purchased online, and the percentage of low priced products (below $25 or €23) involved. Results showed significant differences between online shopping and purchasing behaviors between French and U.S. online shoppers.

A Study on Social Media Strategies Om Online Shopping Cart

The study examines the impact of social media strategies on online shopping cart abandonment Using a sample 245 online shoppers , we analyze the effectiveness of various social media strategies in reducing cart abandonment rates. we employ u-test ,h-test, and correlation analysis to evaluate the relationship between social media engagement and cart abandonment. our findings suggest that certain social media strategies significantly influence online shopping behavior , providing valuable insights for e-commerce businesses. Future flow technologies refers to a range of emerging technologies that are expected to shape the future of online shopping. These may include artificial intelligence (AI) for personalized shopping experiences, augmented reality (AR) for virtual try- ons , and chat bots for customer service. These technologies aim to enhance user experience, increase conversion rates, and reduce cart abandonment by providing more engaging and efficient shopping experiences.

Empowering E-Commerce: Revolutionizing Inventory Management with Seamless API Integration

In today's dynamic e-commerce markets, effective inventory management is crucial for businesses to thrive. This paper explores the transformative potential of integrating Inventory Management APIs with e-commerce websites to streamline operations, enhance customer satisfaction, and maximize profitability. Beginning with an overview of the challenges posed by traditional inventory management methods in the digital age, we delve into the motivations behind adopting Inventory Management APIs and their alignment with the objectives of modern enterprises. Through a comprehensive literature review, we highlight the key dimensions of consumer behavior in online shopping and their implications for inventory management strategies. The methodology section outlines a systematic approach to developing an e-commerce website seamlessly integrated with an Inventory Management API, emphasizing agile principles and iterative development. Challenges and limitations associated with API reliability, data synchronization, scaling, and security are discussed, alongside strategies for mitigating these challenges. The results section showcases the tangible outcomes of the integration, including improved user experience, operational efficiency, and inventory accuracy. Looking ahead, the paper identifies future directions for geographical expansion, enhanced personalization, community features, mobile app optimization, integration of emerging technologies, and advanced analytics. In conclusion, the integration of Inventory Management APIs with e-commerce websites marks a significant milestone in redefining the standards for online retail, offering a comprehensive solution that combines user-friendly interfaces with robust inventory management capabilities. The findings underscore the importance of a holistic approach to e-commerce, addressing both customer-facing aspects and back-end complexities to drive sustainable growth in the digital marketplace.

Online Impulsive Buying Behavior of Mobile Site Shoppers in Turkey: A Mediation Analysis

Objective: The study investigates the correlation between mobile site quality (MSQ) factors and perceived enjoyment. It also explores the link between perceived enjoyment and both electronic word-of-mouth (eWOM) and online impulsive buying behavior of mobile site shoppers in Turkey. Theoretical Framework: The theoretical framework considers MSQ factors (contact, responsiveness, efficiency, fulfillment, and privacy), perceived enjoyment, eWOM and online impulsive buying behavior. Method: This study employs a quantitative methodology, utilizing a questionnaire as the primary data collection tool, designed for a sample size of 676 individuals fromTurkey selected through Purposive Sampling technique. The data analysis method employed is Structural Equation Modeling (SEM), utilizing the AMOS software to assess the goodness of fit statistics of the measurement model with the empirical data. Results and Discussion: The results showed that the contact, efficieny, and the privacy of mobile site influence perceived enjoyment positively. Perceived enjoyment influences both eWOM and online impulsive buying behavior positively and finally eWOM influences online impulsive purchasing behavior positively as well. Research Implications: The results suggest that improvements in MSQ factors of the contact, efficieny, and the privacy can provide mobile site shoppers more enjoyment and while perceived enjoyment has been increasing the probability of mobile site shoppers’ impulsive buying behavior, it also provides more effective marketing campaigns with less costs for the mobile retailers in Turkey. Originality/Value: This study makes a significant contribution to the existing online impulsive behavior literature by focusing on the MSQ elements of mobile shopping sites among shoppers in Turkey. It examines the mediation of perceived enjoyment between all MSQ elements and online impulsive buying behavior, as well as eWOM between perceived enjoyment and online impulsive buying behavior, which have not been extensively explored in prior research.

Exploring the impacts of ecommerce activities on the spatial resilience of warehouse clubs: the role of retail agglomeration

PurposeAs ecommerce becomes more prevalent, traditional brick-and-mortar retailers such as warehouse clubs (WCs) face the challenging task of maintaining and growing their customer base. This study aims to unravel the combined impact of retail agglomeration and ecommerce activities on consumer foot traffic (also referred to as “footprint”) at WC stores, placing an emphasis on the locational strategies adopted by WCs in this evolving retail landscape.Design/methodology/approachMobile-based customer foot traffic data for Costco, a major U.S. WC chain, is sourced for our analysis. We use Principal Component Analysis (PCA) to identify dimensions of general merchandise (GM) and narrow-range merchandise (NM) retail agglomeration. Two-stage least squares (2SLS) regressions are used to explore how the intensity of ecommerce activities and WC locational choices within retail agglomerations impact WC foot traffic.FindingsOur analysis highlights a notable decline in WC store visits attributable to both GM and NM ecommerce activities, with GM ecommerce presenting a more significant competitive challenge to WCs. Regarding retail agglomerations, proximity to GM clusters that include a diverse range of supercenters, department stores, and club stores, is associated with an increase in WC customer visits within their vicinity. In contrast, the influence of NM agglomerations is mixed; clusters adjacent to grocery stores lead to higher WC customer traffic compared to those focused on other specialized stores. These findings underscore the strategic importance of location in mitigating the adverse effects of ecommerce competition. Additionally, our study uncovers intricate dynamics between GM and NM retail clusters and ecommerce activities, demonstrating varied impacts on WC customer footprint.Research limitations/implicationsAccess to customer footprint data illustrates the potential of this data source for retail decision making and researchers. Our analysis is limited to one chain, notably Costco.Practical implicationsOur findings underscore the need for retailers to adeptly navigate the evolving retail landscape, including the confluence between physical and digital retail environments, to secure future success. In particular, our results emphasize the benefits of locating stores within mixed retail agglomerations and underline the need to consider the broader retail landscape in location decisions.Social implicationsThe rise of ecommerce in the U.S. has reshaped consumer behavior and altered local shopping districts’ communal dynamics. This change may spur policy interventions to help physical stores compete with online retailers, emphasizing the importance of retail diversity and community-centric environments to sustain communal retail interactions amidst digital advancements.Originality/valueThe paper makes use of a unique dataset to provide a first assessment of the combined effects of retail agglomeration and ecommerce activities on consumer foot traffic for WC retailers. Thus, this paper provides insights into the impacts on consumer shopping behavior from the dynamic interactions between physical retail clusters and online shopping behaviors.

Deep Learning-Driven E-Commerce Marketing Communication for Recommending Shopping System and Optimizing User Experience

As competition in the realm of e-commerce escalates, the provision of personalized and precise shopping recommendations emerges as a pivotal strategy for e-commerce platforms striving to engage users effectively. Traditional recommendation systems often grapple with challenges such as the inability to capture intricate relationships, limited personalization, and issues concerning diversity. In response to these challenges, this study introduces cutting-edge deep learning techniques, namely Transformer models, Generative Adversarial Networks (GANs), and reinforcement learning, with the aim of bolstering the recommendation accuracy and user experience within e-commerce shopping systems.Initially, we harness Transformer models, capitalizing on their exceptional performance in processing sequential data to adeptly extract and learn representations of both product and user features. This facilitates a more profound understanding of the correlations between products and user shopping behaviors, thus empowering the system to offer more tailored recommendations.

The Factors Affecting Consumers Buying Behaviour Towards Gold Jewellery in Chennai

This consider clarifies around the variables influencing buyer buying behavior towards gold adornments in Chennai, India. Chennai, a city with a wealthy social legacy and gives significance to gold, gives a distinctive advertise for understanding shopper inclinations in this industry. Marketers endeavor to get a handle on this conduct so they can way better define suitable showcasing boost that will result in expanded deals and brand dependability. Purchase motivation of consumer in jewellery sector depends on the internal variables such as Prevailing of the brand, Trust in the brand, Impact of any occasions like Festivals, Birthday, Anniversary, Wedding, Engagement etc., Celebrity Endorsement, Campaign, Brand Image, Exhibitions, Launch of new collection. Analyzing the writing from shopper behavior and showcasing, this investigate finds out a few key variables progressing obtaining choices. Certain esteem develops as a significant determinant, where buyers evaluate gold adornments not as it were as a product but too as an venture and image of status. The notoriety of brands for quality and genuineness, along with individual inclinations and social impacts, encourage choose buyer choices. Furthermore, knowledge of quality, comfort, and viable showcasing techniques plays the major part in choosing shopper obtaining behavior.

Grocery Shopping and Food Preferences: The Long and Winding Road of the COVID-19 Pandemic

The COVID-19 pandemic compelled many consumers to adapt their grocery shopping, food preferences, and consumption behaviors. Based on 18 in-depth interviews with adults in the United States, this study uses a liminality framework to explore how the pandemic altered these behaviors. It also seeks to assess whether individuals have reverted to pre-pandemic consumption behaviors. Results show the mode of grocery shopping shifted; the frequency of grocery shopping declined; and the quantity of food increased in the initial stages of the pandemic with more people remaining home. By summer 2022, more individuals had shifted to online grocery shopping from shopping in-person, a departure from their pre-pandemic behavior. Findings also indicate the frequency of shopping largely mirrors pre-pandemic levels, though the quantity of groceries purchased has declined. Finally, the decline in food purchases is accompanied by increased spending on groceries in all phases of the pandemic.

The Impact of Social Media Advertising on Consumer Purchase Decisions

Social media has risen as an effective stage for promoting, impacting shopper behaviors and buying choices universally. This considers points to investigate the effect of social media publicizing on customer buy choices, analyzing the components through which social media campaigns influence buyer inclinations, demeanors, and eventually, buying behavior. The investigation utilizes a mixed-methods approach, combining quantitative investigation of buyer studies with subjective examination of social media advertisement substance and engagement measurements. Key components such as advertisement significance, validity, personalization, and social impact are explored to get their part in forming customer discernments and choices. Discoveries uncover that compelling social media promotion altogether impacts buyer buy choices by making mindfulness, improving brand engagement, building belief, and leveraging social supports. Besides, the study reveals the significance of focused on publicizing techniques, intuitive substance, and consumer-generated input in driving positive customer reactions and cultivating brand devotion. The suggestions of these discoveries amplify to marketers, sponsors, and businesses looking for to optimize their social media promoting techniques to viably reach and lock in their target group of onlookers, improve brand discernment, and drive change rates. Future investigate headings are proposed to dig deeper into particular industry settings, buyer sections, and developing social media patterns to improve our understanding of the energetic exchange between social media promotion and customer behavior.

Dampak Live Streaming, Celebrity Endorsement, Alat Promosi, Review Online, Keamanan, Kemudahan Penggunaan dan Kenyamanan terhadap Perilaku Belanja Pakaian Online pengguna Tiktok setelah Pandemi Covid-19 di Jakarta

This research aims to determine the significant influence of several factors on the online shopping behavior of TikTok users during the Covid-19 pandemic in Jakarta. This research used the Structural Equation Modeling Partial Least Squares (SEM-PLS) method with a total of 215 respondents. The data that has been collected is processed using the SmartPLS application, ensuring accurate statistical analysis. The research results show that all the variables studied have a significant influence on the online shopping behavior of TikTok users during the pandemic in Jakarta. Of all the factors observed, online reviews emerged as the most influential variable and played an important role in shaping users' purchasing decisions. In contrast, the variable that has the least influence is security, indicating that although important, security factors have a more limited impact in influencing TikTok users' online shopping decisions. In conclusion, this research provides important insights into the factors that influence TikTok users' online shopping behavior during the pandemic. Keywords: Celebrity Endorsement, Live Streaming, Promotional Tools

The Effect of E-service Quality and Customer Satisfaction and Trust to Customer Online Shopping Behavior

China's e-commerce sector is experiencing rapid growth. Among Chinese cities, Beijing stands out with its robust development, consistently ranking among the top three in the nation. Nonetheless, Beijing's e-commerce enterprises encounter various challenges. This research endeavors to examine the interplay between e-service quality, customer satisfaction, trust, and online shopping behavior within the Beijing e-commerce landscape. Descriptive method was considered by the researchers. The respondents of the study are the users of online shopping platforms that operates in Beijing China who have experience using major online consumption platforms. The sample size is 385 people which was calculated by Raosoft software. The respondents of the study were chosen using the simple random sampling design. Moreover, constructed survey questionnaires served as a tool with five-key point Likert scale. The Statistical Package for Social Sciences (SPSS) was employed in the statistical analysis of data. The following statistical tools were used in the study: frequency and percentage, mean, reliability and validity analysis, Analysis of Variance and Multiple Linear Regression. The study resulted in a strong positive relationship between customer satisfaction, trust and over-all e-service quality. Specifically, customer satisfaction and trust resulted in a very strong relationship to customer behaviors. For the comparison of means when grouped according to profile variables, customer satisfaction level and over-all e-service quality have a significant difference when grouped to frequency of purchase. Based on the results of the study, the researchers proposed a development program to help improve the quality of e-services and thus increase customer re-purchase rates.

Influence of maternal past non-transport pro-environmental behaviours on young adults’ sustainable transport

This UK-focused longitudinal study examines the influence of maternal past non-transport, pro-environmental actions (e.g. eco-friendly shopping and energy-saving behaviours during their children’s adolescence) on children’s sustainable transport behaviours as young adults. It also explores the role of children's pro-environmental attitudes as young adults in this influence. Structural equation modelling was used to explore these complex interactions based on data from 977 mother–child pairs in waves 4 and 10 of the UK Household Longitudinal Study. Findings reveal that maternal past non-transport, pro-environmental behaviours positively influence children’s pro-environmental attitudes as young adults. While no direct influence of these maternal behaviours on children’s sustainable transport behaviours as young adults was found, an indirect influence was observed, mediated through children’s pro-environmental attitudes as young adults. This study not only provides a new perspective for understanding the origins of sustainable transport behaviours in young adults, but also reveals pathways of intergenerational transmission of pro-environmental behaviours.

SOCIAL MEDIA INFLUENCERS ON CONSUMER BEHAVIOUR

The think about the complex intuitive that exist between social media influencers and shopper behavior in the present day advanced world, highlighting the imperative part that influencers play in impacting client inclinations, buying choices, and sees of brands. The inquire about looks at how influencers influence buyer conduct utilizing a mixed-methods approach that incorporates studies, interviews, and quantitative examination of social media engagement measurements. It emphasizes relatability, believe, and realness as significant components in building connections between influencers and their adherents. The victory characteristics of influencer showcasing campaigns, moral issues counting straightforwardness and genuineness, the maintainability of influencer showcasing in the confront of changing social media patterns, and the plausibility of influencer weakness are a few of the major subjects that were inspected. This think about includes to the body of information as of now in presence, which makes a difference marketers, businesses, and governments explore the ever-changing world of advanced showcasing in the twenty-first century. Keywords: Influencer weakness, Advanced showcasing, Social media engagement measurements, Influencer promoting campaigns, Buyer behavior, Social media influencers

CONSUMER BEHAVIOURL ANALYSIS IN E COMMERCE AS MYNTRA USING DATA ANALYTICS

CONSUMER BEHAVIOURL ANALYSIS IN E COMMERCE AS MYNTRA USING DATA ANALYTICS

Analysis of Paylater Usage on Impulsive Buying Behavior

Analysis of Paylater Usage on Impulsive Buying Behavior

Profiling consumers’ online shopping and following social media influencers behaviors

In order to develop effective digital marketing strategies, this study explores how demographic factors may affect consumers’ online shopping and following social media influencers behaviors. Market segmentation theory and consumer demographics theory provide the theoretical foundation for this study. By analyzing survey data collected from 6,034 U.S. adults with decision tree analysis, there are a number of significant findings. First, educational level, income, and age category are the important predictors for consumers’ buying things online using a desktop or laptop computer behavior. Second, age category, geographic location (urban, suburban, rural) are the predictors for consumers’ buying things online using a smartphone behavior. Third, educational level, age, and geographic location are the predictors for consumers’ preferring online shopping over in-store shopping behavior. Fourth, age category and race-ethnicity are the predictors for following social media influencers behavior. Fifth, gender and age category are the predictors for purchasing something after seeing an influencer’s posts behavior. Finally, age category and gender are the predictors for purchase decisions getting impacted by influencers. The results provide valuable insights about consumer behaviors online, market segmentation, and influencer marketing strategies.